Use this workflow to monitor LinkedIn keyword engagement and turn relevant activity into actionable signals inside lemlist.
By the end of this tutorial, you’ll know how to create a signal agent that tracks engagement around specific LinkedIn keywords, narrow it to the right audience, exclude unwanted companies, choose how signals should be processed, and review the setup before launch.
Why this matters
A LinkedIn keywords signal agent helps you spot people and companies already engaging with subjects related to your offer. That means you can prioritize warmer leads, focus your outreach, and automate follow-up based on real buying intent instead of guessing. If you monitor All segments, you can also exclude company lists such as current customers, partners, or do-not-contact accounts so your signals stay focused on net-new opportunities.
Prerequisites
You should already know the basics of navigating Signal agents in lemlist.
You should already have access to the Signal agents feature and enough credits for LinkedIn keyword monitoring.
You should already know which LinkedIn keywords, industries, or buyer signals matter most to your team.
If you plan to push signals to a campaign automatically, you should already have at least one campaign ready to use.
Core lesson — step-by-step workflow
Phase 1: Start a new signal agent
Go to Signal agents from the left sidebar, then click Create signal agent. This opens the builder, where you’ll define the signal you want to detect and how lemlist should act on it.
In the Signal to detect step, expand Social activity, choose LinkedIn keywords, then continue. This signal is useful when you want to find people or companies already interacting with content around your space, which is often a strong indicator of interest.
Phase 2: Configure the LinkedIn keywords you want to track
Add a clear Agent name so your team can quickly understand what this signal agent monitors.
Under LinkedIn keywords to monitor, enter one keyword per line, then click Add keywords. This tells lemlist exactly which LinkedIn conversations to watch.
Choose the Types of engagement to track. You can monitor:
Posts — track people posting about your selected keywords
Likes on their posts — track people liking posts about those keywords
Comments on their posts — track people commenting on posts about those keywords
This choice matters because it shapes the intent level of the leads you’ll surface. For example, comments often indicate deeper engagement than likes.
If needed, add Excluded keywords so irrelevant topics do not trigger your agent. Enter one excluded keyword per line, then click Add excluded keywords.
Phase 3: Define the scope you want to monitor
In the Scope step, choose whether the agent should monitor All segments or a narrower audience using Criteria. Use this step to control whether you want broad discovery or a more focused workflow tied to your ideal customer profile.
If you want more precision, add criteria such as Personas, Locations, Industries, and Company sizes. These filters help you avoid collecting activity from people outside your target audience.
You can also use the Exclusion list to remove engagement from specific companies. This is especially helpful if you want to exclude current customers, partners, competitors, or known low-fit accounts before signals start flowing in.
Set the Maximum number of signals identified per day to control daily volume and credit usage. lemlist also shows the estimated daily and monthly credit impact so you can adjust the limit before moving forward.
Keep in mind that broader scope settings can generate more signals and use more credits, so it’s best to start with a focused setup and expand only if needed.
Phase 4: Choose how lemlist should process signals
In Signals processing, decide what should happen when lemlist identifies a matching signal. You can:
Review signals manually
Auto-create tasks
Auto-push to campaign
If you want task-based follow-up, select Auto-create tasks and configure the task details.
If you want a more hands-off workflow, select Auto-push to campaign and choose the campaign that should receive those leads. You can also decide whether to include contacts already linked to existing signals and how to handle leads already present in another campaign.
Phase 5: Review and launch the signal agent
Open the Summary step and review all sections carefully, including the signal type, monitored keywords, excluded keywords, engagement type, billing impact, processing method, and scope settings. This final check helps you catch costly mistakes before the signal agent starts running.
When everything looks correct, click Deploy agent to launch the signal agent.
Practical application / real-life example
Here’s a simple example for a sales team selling outbound software:
Keywords to monitor: sales prospecting, outbound, b2b saas
Excluded keyword: inbound
Engagement type: Likes on their posts
Segment filters: Heads of Sales, B2B SaaS, specific locations, and mid-market company sizes
Exclusions: competitors, your own company, current customers
Processing: Auto-push matched leads into a dedicated campaign automatically
This setup works well when you want to identify people already interacting with keywords related to your solution and move them into outreach quickly, without clutter from accounts you already work with.
Troubleshooting & pitfalls
Issue: I’m not seeing any signals yet
Root cause: New signal agents can take time to populate, or your filters may be too narrow.
Fix:
Wait a little longer if the signal agent was just created
Review your keyword list and make sure the keywords are broad enough to generate activity
Temporarily reduce filtering criteria like industry, company size, or exclusions
Issue: My signal agent is using too many credits
Root cause: A broad scope or a high daily identification limit can increase credit usage.
Fix:
Lower the maximum number of signals identified per day
Keep only the most relevant keywords
Use audience filters to improve quality instead of widening the scope
Issue: The leads aren’t relevant
Root cause: Your keywords may be too broad, or the agent isn’t limited to the right scope.
Fix:
Replace generic keywords with more specific buying-intent terms
Add location, industry, or company size filters
Use excluded keywords to remove unrelated conversations
Use the exclusion list for companies you never want to track
Issue: Leads are not being pushed into the right campaign
Root cause: The wrong processing option or campaign was selected during setup.
Fix:
Go back to the Signals processing step
Confirm that Auto-push to campaign is selected if automation is your goal
Check the chosen campaign and review how duplicates or existing campaign members should be handled
Issue: Important companies are being excluded or missed
Root cause: The scope criteria or exclusion list may be too restrictive.
Fix:
Review all filters in the Scope step
Double-check excluded company URLs for typos or unnecessary entries
Test with a broader version of the signal agent first, then narrow it gradually